Metadata-Version: 1.1
Name: scikit-tensor
Version: 0.1
Summary: Python module for multilinear algebra and tensor factorizations
Home-page: http://github.com/mnick/scikit-tensor
Author: ('Maximilian Nickel',)
Author-email: mnick@mit.edu
License: GPLv3
Download-URL: http://github.com/mnick/scikit-tensor
Description: scikit-tensor
        =============
        
        scikit-tensor is a Python module for multilinear algebra and tensor
        factorizations.
        
        Dependencies
        ------------
        
        The required dependencies to build the software are ``Numpy >= 1.3``,
        ``SciPy >= 0.7``.
        
        Usage
        -----
        
        Example script to decompose sensory bread data (available from
        http://www.models.life.ku.dk/datasets) using CP-ALS
        
        .. code:: python
        
            import logging
            from scipy.io.matlab import loadmat
            from sktensor import dtensor, cp_als
        
            # Set logging to DEBUG to see CP-ALS information
            logging.basicConfig(level=logging.DEBUG)
        
            # Load Matlab data and convert it to dense tensor format
            mat = loadmat('../data/sensory-bread/brod.mat')
            T = dtensor(mat['X'])
        
            # Decompose tensor using CP-ALS
            P, fit, itr, exectimes = cp_als(T, 3, init='random')
        
        References
        ----------
        
        If you use ``scikit-tensor`` in your research, please cite
        
        ::
        
            Maximilian Nickel. scikit-tensor Library (Version 0.1). Available Online, November 2013.
        
        Install
        -------
        
        This package uses distutils, which is the default way of installing
        python modules. To install in your home directory, use
        
        ::
        
            python setup.py install --user
        
        To install for all users on Unix/Linux
        
        ::
        
            python setup.py build
            sudo python setup.py install
        
        To install in development mode
        
        ::
        
            python setup.py develop
        
        Contributing & Development
        --------------------------
        
        scikit-tensor is still an extremely young project, and I'm happy for any
        contributions (patches, code, bugfixes, *documentation*, whatever) to
        get it to a stable and useful point. Feel free to get in touch with me
        via email (mnick at AT mit DOT edu) or directly via github.
        
        Development is synchronized via git. To clone this repository, run
        
        ::
        
            git clone git://github.com/scikit-learn/scikit-learn.git
        
        Authors
        -------
        
        Maximilian Nickel
        
        -  http://twitter.com/mnick
        -  http://github.com/mnick
        
        License
        -------
        
        scikit-tensor is licensed under the GPLv3
        http://www.gnu.org/licenses/gpl-3.0.txt
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
